How to connect Google Cloud Storage and Google Cloud BigQuery (REST)
Create a New Scenario to Connect Google Cloud Storage and Google Cloud BigQuery (REST)
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud Storage, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud Storage or Google Cloud BigQuery (REST) will be your first step. To do this, click "Choose an app," find Google Cloud Storage or Google Cloud BigQuery (REST), and select the appropriate trigger to start the scenario.

Add the Google Cloud Storage Node
Select the Google Cloud Storage node from the app selection panel on the right.


Google Cloud Storage

Configure the Google Cloud Storage
Click on the Google Cloud Storage node to configure it. You can modify the Google Cloud Storage URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Cloud BigQuery (REST) Node
Next, click the plus (+) icon on the Google Cloud Storage node, select Google Cloud BigQuery (REST) from the list of available apps, and choose the action you need from the list of nodes within Google Cloud BigQuery (REST).


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Authenticate Google Cloud BigQuery (REST)
Now, click the Google Cloud BigQuery (REST) node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud BigQuery (REST) settings. Authentication allows you to use Google Cloud BigQuery (REST) through Latenode.
Configure the Google Cloud Storage and Google Cloud BigQuery (REST) Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud Storage and Google Cloud BigQuery (REST) Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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AI Anthropic Claude 3
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Google Cloud BigQuery (REST)
Trigger on Webhook
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud Storage, Google Cloud BigQuery (REST), and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud Storage and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Google Cloud Storage and Google Cloud BigQuery (REST) (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud Storage and Google Cloud BigQuery (REST)
Google Cloud Storage + Google Cloud BigQuery (REST) + Google Sheets: When a new log file is uploaded to Google Cloud Storage, this flow triggers a BigQuery job to analyze the data. The results are then inserted into a Google Sheet for visualization and dashboard updates.
Google Cloud BigQuery (REST) + Google Cloud Storage + Slack: This automation monitors BigQuery costs by running a query. If spending exceeds a defined threshold, error logs are stored in Google Cloud Storage, and a Slack message is sent to the finance team.
Google Cloud Storage and Google Cloud BigQuery (REST) integration alternatives

About Google Cloud Storage
Use Google Cloud Storage in Latenode for automated file management. Upload, download, and manage files in your workflows. Automate backups, data archiving, or image processing. Connect GCS to other apps for seamless data transfer and triggering events. Latenode's visual editor simplifies complex file-based automations.
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About Google Cloud BigQuery (REST)
Automate BigQuery data workflows in Latenode. Query and analyze massive datasets directly within your automation scenarios, bypassing manual SQL. Schedule queries, transform results with JavaScript, and pipe data to other apps. Scale your data processing without complex coding or expensive per-operation fees. Perfect for reporting, analytics, and data warehousing automation.
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FAQ Google Cloud Storage and Google Cloud BigQuery (REST)
How can I connect my Google Cloud Storage account to Google Cloud BigQuery (REST) using Latenode?
To connect your Google Cloud Storage account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Storage and click on "Connect".
- Authenticate your Google Cloud Storage and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate data backups from storage to BigQuery?
Yes, you can! Latenode lets you automate backups with a visual interface and scheduled triggers, ensuring data safety and integrity with no coding required. Scale on demand.
What types of tasks can I perform by integrating Google Cloud Storage with Google Cloud BigQuery (REST)?
Integrating Google Cloud Storage with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Automatically loading CSV files from storage into BigQuery tables.
- Creating data pipelines for real-time analytics and reporting.
- Archiving older datasets in storage and updating BigQuery.
- Enriching data in BigQuery with files stored in Cloud Storage.
- Triggering data transformation workflows based on storage events.
How secure is my data when transferring between services?
Latenode uses secure connections and follows best practices to protect your data. OAuth ensures safe access without sharing sensitive credentials.
Are there any limitations to the Google Cloud Storage and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large file transfers might require optimized configurations.
- Complex data transformations may benefit from JavaScript blocks.
- API rate limits on either service can impact workflow speed.